Novel biomarker panel measuring endothelial injury identifies patients at risk of coronary artery syndrome and discordance with low-density lipoprotein cholesterol.

Background: Individuals with no history of coronary artery disease can develop acute coronary syndrome (ACS), often in the absence of major risk factors including low-density lipoprotein cholesterol (LDL-C). We identified risk factors and biomarkers that can help identify those at discordantly high risk of ACS with normal LDL-C using a novel validated coronary artery disease predictive algorithm (CADPA) incorporating biomarkers of endothelial injury.

Methods: Five-year predicted ACS risk was calculated for 6392 persons using CADPA. Persons were classified as low (<3.5%), intermediate (3.5-<7.5%) or high (≥7.5%) CADPA risk and by LDL-C levels <130 mg/dL (low) and ≥130 mg/dL (high) and whether in the discordantly low LDL-C (but high CADPA risk) or high LDL-C (but low/intermediate CADPA risk) group. Multiple logistic regression identified risk factors and biomarkers that predicted discordance.

Results: 31% were classified as low (<3.5%), 27% at intermediate (3.5-<7.5%) and 42% were at high risk (≥7.5%). 28% of subjects were identified in the low LDL discordant risk group (LDL-C< 130 mg/dL but 5-year CADPA predicted risk ≥7.5%) and 19% in the high LDL discordant risk group (LDL-C ≥ 130 mg/dL but 5-year CADPA risk of <7.5%). Diabetes (odds ratio [OR], 2.84 [2.21-3.66]), male sex (OR, 2.83 [2.40-3.35]), family history (OR, 2.23 [1.88-2.64]) and active smoking (OR, 1.99 [1.50-2.62]) predicted low LDL risk discordance more than other risk factors (all P < 0.01). Increased serum soluble FAS, hemoglobin A1c and interleukin-16 were the biomarkers most independently associated with increased risk.

Conclusions: Discordance between LDL-C levels and ACS risk is common. Males with diabetes and a family history of myocardial infarction who are actively smoking may be at highest risk of developing ACS despite controlled LDL-C. Future studies should examine whether using the CADPA can help identify individuals that could benefit from earlier targeting of risk factor modification for the prevention of ACS.